Artificial intelligence in bone age assessment: accuracy and efficiency of a novel fully automated algorithm compared to the Greulich-Pyle method
Artificial intelligence in bone age assessment: accuracy and efficiency of a novel fully automated algorithm compared to the Greulich-Pyle method
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DOI：
10.1186/s41747-019-0139-9
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发表时间：
2020-01-28
影响因子：
3.8
通讯作者：
Bodelle, Boris
中科院分区：
文献类型：
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作者：
Booz, Christian;Yel, Ibrahim;Bodelle, Boris
人工智能（AI）进行的骨龄（BA）评估由于在日常生活中提高了准确性、精确度和时间效率而越来越受到关注。本研究的目的是调查一种新的人工智能软件版本的准确性和效率的自动BA评估相比，Greulich-Pyle方法。方法对514例患者的X线片进行回顾性分析。总BA由三名盲态放射科医生应用GP方法和AI软件独立评估。比较了两种方法的总体和性别特异性BA评估结果以及阅读时间，而参考BA由两名经验丰富的盲态儿科放射科医生通过应用Greulich-Pyle方法达成共识。结果AI计算的BA与参考BA之间的平均绝对偏差（MAD）和均方根偏差（RSMD）（MAD 0.34年，RSMD 0.38年）显著低于读片者计算的BA与参考BA之间的平均绝对偏差（MAD 0.79年，RSMD 0.89年; p < 0.001）。AI推导的BA与参考BA之间的相关性（r = 0.99）显着高于读者计算的BA与参考BA之间的相关性（r = 0.90; p < 0.001）。关于性别，阅片者一致性和相关性分析无统计学差异（p = 0.241）。使用AI系统，平均阅读时间减少了87%。结论一种新的AI软件可以实现高度准确的自动BA评估。与Greulich-Pyle方法相比，它可以通过减少阅读次数而不影响准确性来提高临床常规的效率。
Background Bone age (BA) assessment performed by artificial intelligence (AI) is of growing interest due to improved accuracy, precision and time efficiency in daily routine. The aim of this study was to investigate the accuracy and efficiency of a novel AI software version for automated BA assessment in comparison to the Greulich-Pyle method. Methods Radiographs of 514 patients were analysed in this retrospective study. Total BA was assessed independently by three blinded radiologists applying the GP method and by the AI software. Overall and gender-specific BA assessment results, as well as reading times of both approaches, were compared, while the reference BA was defined by two blinded experienced paediatric radiologists in consensus by application of the Greulich-Pyle method. Results Mean absolute deviation (MAD) and root mean square deviation (RSMD) were significantly lower between AI-derived BA and reference BA (MAD 0.34 years, RSMD 0.38 years) than between reader-calculated BA and reference BA (MAD 0.79 years, RSMD 0.89 years; p < 0.001). The correlation between AI-derived BA and reference BA (r = 0.99) was significantly higher than between reader-calculated BA and reference BA (r = 0.90; p < 0.001). No statistical difference was found in reader agreement and correlation analyses regarding gender (p = 0.241). Mean reading times were reduced by 87% using the AI system. Conclusions A novel AI software enabled highly accurate automated BA assessment. It may improve efficiency in clinical routine by reducing reading times without compromising the accuracy compared with the Greulich-Pyle method.